code: def reparameterize_model(model: torch.nn.Module) -> nn.Module:
      """Method returns a model where a multi-branched structure
          used in training is re-parameterized into a single branch
          for inference.
  
      Args:
          model: MobileOne model in train mode.
  
      Returns:
          MobileOne model in inference mode.
      """
      # Avoid editing original graph
      model = copy.deepcopy(model)
      for module in model.modules():
          if hasattr(module, "reparameterize"):
              module.reparameterize()
      return model
  
file_path: ml-fastvit/models/modules/mobileone.py
imports: from typing import Union, Tuple
  import copy
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 for calling a global function with example usage: reparameterize_model(model) and returns: model